تحلیل فضایی مخاطرات محیطی

تحلیل فضایی مخاطرات محیطی

شبیه‌سازی رواناب ناشی از ذوب برف حوضه گاماسیاب با مدل SRM

نویسندگان
دانشگاه تبریز
چکیده
تامین منابع آب توسط برف در حوضه­های کوهستانی بعلت خاصیت تاخیر در ایجاد رواناب، ضروری است. بنابراین شبیه­سازی رواناب ناشی از ذوب برف و تغییرات فصلی پوشش آن در مدیریت منابع آب بسیار اهمیت دارد. در این مطالعه، به­منظور برآورد رواناب حاصل از ذوب برف در حوضۀ گاماسیاب، نخست سطح پوشش برف برای سال­های آبی 95 الی 97 با استفاده از تصاویر روزانۀ ماهوارۀ ترا- مودیس با تفکیک مکانی 1 کیلومتر از طریق سامانه گوگل ارث انجین استخراج شد. سپس در محیط نرم­افزارGIS ، مشخصات فیزیوگرافی حوضه به­دست آمد. در مرحلۀ بعد، با واردکردن داده­های پوشش برف، متغیرهای هواشناختی و شاخص­های لازم به مدلSRM ، رواناب ناشی از ذوب برف شبیه­سازی شد. در این شبیه­سازی سال 95-96 برای واسنجی و سال 96-97 جهت اعتبارسنجی مدل در نظر گرفته شد. نتایج نشان داد که، سهم جریان رودخانه از ذوب برف در ماه­های اسفند و فروردین­ماه چشمگیر است، ولی با افزایش درجه­حرارت هوا در اردیبهشت­ماه، سهم باران در جریان پررنگ­تر می­شود. همچنین نتایج شبیه­سازی بیانگر دقت بالای این مدل می­باشد، به­طوری که ضریب تعیین (R2) برای سال­های آبی 95-96 الی 96-97 به ترتیب معادل 93/0 و 9/0 و درصد خطای حجمی آن نیز به ترتیب (DV) 3/0 و 33/3 به­دست آمد.
کلیدواژه‌ها

عنوان مقاله English

Simulation of runoff from Gamasiab basin snowmelt with SRM model

نویسندگان English

Mohammad Hossein aalinejad
Saeed Jahanbakhsh ASL
University of Tabriz
چکیده English





Simulation of runoff from Gamasiab basin snowmelt with SRM model





Abstract

Snow cover in a basin affect its water balance and energy balance. So, snow cover variation is a major factor in climate change of a region. Study of temporal variation of snowmelt and snow water equivalent depth is very important in flood forecasting, reservoir management and agricultural activities of an area. In the most of the mountainous basins of the country, information on snow cover were not available. Also, the number of meteorological stations in high altitude areas do not match with information needed for snowmelt simulation. Therefore, indirect methods such as the analysis of satellite images to obtain the needed parameters for simulation is necessary, which is the one of the most effective methods in estimation of runoff originated from snow. Using the NOAA satellite data for zoning the snow cover of area started firstly in the USA since the 1961 and continuous until today (spatial and temporal resolution of satellite images increased by starting the MODIS work).

Gamasiab River is one of the important branches of Karkheh basin. Its basin area is about 11040 km2 between latitude 47 degrees 7 minutes to 49 degrees 10 minutes east and latitude 33 degrees 48 minutes 4 degrees 85 minutes north. The altitude of this basin is 1275 to 3680 meters above sea level. In this study, for simulation of runoff originated from melting snow, firstly snow cover in the basin of Gamasiab in 2014 to 2017 calculated by using the satellite images of MODIS in the google earth engine system. Also, air temperature and precipitation data of synoptic stations in the area of study and daily stream flow discharges of Polechehr hydrometric station, from November of 2014 to July of 2017 was used. Then, weather and snow cover area included as the input of SRM for simulation of snowmelt runoff. To obtain the information needed to the model, physiographic characteristics of the basin including the area and different classes of height obtained from the Arc-Hydro and Hec_GeoHMS in DEM maps of GIS software. Then the snow cover areas obtained from the images of MODIS in daily interval that obtained by google earth engine system.

Using the digital elevation map (DEM) and the accession of the Arc-Hydro and Hec_GeoHMS software of GIS, firstly flow direction map plotted. Secondly flow accumulation and stream flow network maps plotted, and by introducing the basin output to the program (Polechehr hydrometric station) borders of the basin identified and classification of the basin accomplished according to the three distinct height classes. Monitoring the snow surface cover during the daily time interval showed that the area covered with snow in winter season. This area decreases as the air temperature increases. The SRM model simulated the snowmelt of Gamasiab basin with good accurately, in which, the percent of volume error or Vd was lose than 2% and the R2 was above 0.9.

The results of this research showed that the using the images of MODIS yields a reasonable estimation of the snow cover area of Gamasiab with local of data. Also simulation results showed the high capability of the SRM in snowmelt runoff of the area under study. Result showed that the coefficient of determination and volume percent of error of model was 0.93 and %0.3 for 2014-2015 and it was 0.9 and 3.33 for 2015-2016 years, respectively. The results of this study, was in consistent with the previous studies fading in which in addition of model's parameters, physiographic characteristics, basin play a major role in the accuracy of the simulation. According to the calculated and observed runoff diagram, in both years of study, peak temperatures begin in March, as the weather warms and the snow melts, and will continue until April. Considering the snow cover, it can be concluded that the main runoff of March Peak is related to snowmelt, but with the change in the shape of precipitation from snow to rain and the warming of the weather, April peak is related to rain. Regardless of acceptable simulation results of the model, the lack of snow survey station in the study area, (yield the model to face with difficulty) in process. To overcome this shortcoming, we used the presumptions of the model and recommended values of the model.



Keywords: MODIS; Remote sensing; Runoff Snow; SRM; Gamasiab.

کلیدواژه‌ها English

Snow
Remote Sensing
SRM
MODIS
Gamasiab
10. Adnan, M.; G, Nabi. M, S, Poomee and A, Ashraf. 2017. Snowmelt runoff prediction under changing climate in the Himalayan cryosphere: A case of Gilgit River Basin. Geoscience Frontiers, Volume 8, Issue 5, Pages 941-949.
11. Food and Agriculture Organization .1978. 1977 Production Yearbook: FAO Statistics, vol. 31, Ser. No. 15. Rome: United Nations Food and Agriculture Organization.
12. Hall D.K.; G.A. Riggs and V.V. Salomonson. 1995. Development of methods for mapping global snow cover using moderate resolution imaging spectroradiometer data. Remote Sens. Environ. 54(2):127–140.
13. Hall D.K.; G.A. Tait, V.V. Riggs, J. Salomonson, Y.L. Chien and G.K. Andrew. 1998. Algorithm Theoretical Basis Document (ATBD) for the MODIS Snow-,Lake Ice- and Sea Ice-Mappin Algorithms, modis Algorithm TheoreticalBasis Document Number ATBD-MOD-10,NASA Goddard Space Flight Center.
14. Harshburger B.J., Karen S.H., Von P.W., Brandon C.M. Troy R.B. and Rango A. 2010. Evaluation of short-to-medium range stream flow forecasts obtained using an enhanced version of SRM. Journal of the American Water Resources Association (JAWRA), 15(1):1752-1688.
15. Jones, H. G.; J. W. Pomeroy, D. A Walker and R. W. Hohem .2001. Snow Ecology. Cambridge: Cambridge university press. 2001. 398 p.
16. Malcher, P.; and M, Heidinger.2001. Processing and data assimilation scheme for satellite snow cover products in the hydrological model. Envisnow EVG1-CT- 2001-00052.
17. McCuen R. H.1998. Hydrologic analysis and design. Printice-Hall Pub., Inc. N.J., PP.548.
18. Rango, A.; and J. Martinec. 1998. The snowmelt runoff model (SRM) user/s manual, version 4, URL: fttp // hydrolab. arsusda. gov/ pub / srm / srm4.pdf.
19. Shunping, X.; D. Jinkang, Z. Xiaobing, Z. Xueliang, F. Xuezhi, Z. Wenlong, Li. Zhiguang, Yu Xu Chong. 2018. A progressive segmented optimization algorithm for calibrating time-variant parameters of the snowmelt runoff model (SRM), Journal of Hydrology, Volume 566, Pages 470-483.
20. Seidel, K.; and J, Martinec. 2002. Hydrological applications of Satellite Snow Cover mapping in the swiss Alps. Proceedings of Earsel-Lissig-Workshop Observing Our Cryosphere from Space, Bern, March 11-13.
21. Stephan, H.; 1981. Snow and Agriculture. In The Handbook of Snow, ed. D. M. Gray and D. H. Male, Willowdale, Ontario: Pergamon Press, pp. 60–125.
22. Tekeli, A.E.; Z. Akyurek, A. Sorman, A, Sensoy. and A, Sorman. 2005. Using MODIS snow cover maps in modeling snowmelt runoff process in the easternpart of Turkey. Journal of Remote Sensing of Environment, 97: 216-230.